DevOps Engineer III, AI – Business Automation

Responsibilities

• Design, develop, and maintain full-stack custom business applications including manufacturing execution systems (MES), asset management tools, and unified internal operational dashboards
• Build and maintain software integrations across the company’s internal systems portfolio, including SAP S/4
  
  HANA Cloud Public, SAP Business ByDesign, SAP Concur (Travel, Expense & Invoice), Salesforce, Google Workspace, Zoom, Slack, Jira, Git Hub, and additional platforms as the business evolves
• Serve as the company’s primary subject matter expert on artificial intelligence and key member of the AI Risk Committee
• Design and deploy AI-powered agents and automated workflows using platforms such as Anthropic Claude and Google Gemini to systematically identify and eliminate routine manual tasks across the organization
• Architect and implement prompt engineering strategies, agentic frameworks, and multi-step AI pipelines tailored to specific business use cases and operational requirements
• Continuously evaluate emerging AI tools, LLM capabilities, agent frameworks, and automation platforms; build proof-of-concepts and recommend adoption paths aligned with company objectives and infrastructure
• Establish and maintain internal AI standards, best practices, and responsible use guidelines to ensure consistent, secure, and effective AI adoption across the organization
• Lead cross-departmental discovery sessions to surface automation and AI opportunities, partnering with business stakeholders to translate operational needs into scalable, maintainable technical solutions
• Develop and deliver internal training, documentation, and enablement resources to educate employees on AI tools and capabilities, building a culture of intelligent automation throughout the company
• Build, maintain, and document RESTful APIs and integration middleware connecting internal and external systems
• Review and validate code quality, architectural decisions, and AI/automation design patterns; mentor contributors and help establish team standards as the AI practice grows
• Document systems, integrations, automation logic, and AI agent configurations to ensure maintainability, reliability, and effective knowledge transfer
• Build the foundation for and grow into leading a dedicated AI Automation & Integrations team. Including defining team scope, structure, and technical direction as the practice matures within Business Technology
• Follow all best practices and procedures as established by the Business Technology leadership.

• BS in Computer Science, Software Engineering, Information Technology, or a related field; equivalent professional experience accepted in lieu of degree
• 7+ years of professional experience in software engineering, full-stack development, or a closely related technical discipline
• Demonstrated experience building and deploying production-grade custom applications and software integrations
• Hands-on experience working with AI/LLM APIs and building AI-powered automations, agents, or intelligent workflows
• Experience with full-stack web application development including both frontend and backend components
• Proficiency in full-stack development using Python, JavaScript/Type Script, Node.js, and modern frontend frameworks (e.g., React, Vue)
• Hands-on experience with AI/LLM platforms, specifically Anthropic Claude and Google Gemini APIs, including prompt engineering and agentic workflow design
• Experience designing and building AI agents, multi-step automation pipelines, and intelligent workflow orchestration
• Experience working with and implementing AI MCP servers and integrations
• Strong knowledge of RESTful API design, integration patterns, and automation/iPaaS platforms; experience integrating enterprise systems such as SAP, Salesforce, Google Workspace, Slack, and Jira
• Experience with relational and non-relational database design, configuration, and management
• Familiarity with containerization (Docker), cloud infrastructure, and CI/CD workflows
• Knowledge of Git and collaborative development practices in an agile environment
• Excellent problem-solving, systems-thinking, and troubleshooting skills
• Ability to communicate complex technical concepts clearly to non-technical stakeholders across departments.